Tag:data quality

Articles tagged "data quality".

• 33 MIN READ•Sep 2, 2026

  Great Expectations vs Soda vs dbt Tests: Data Quality Tools

  Great Expectations, Soda, dbt tests and anomaly detection tools compared on check language, where they run, cost, Iceberg metadata use and 2026 vendor changes.

  Great ExpectationsSodadbt
• 31 MIN READ•Oct 5, 2026

  When a Data Agent Gives a Wrong Number: Incident Response for Agentic Analytics

  A plan for when a data agent gives a wrong number: severity levels, containment, Iceberg time travel reproduction, and blast radius queries.

  incident responseAI agentsApache Iceberg
• 31 MIN READ•Sep 28, 2026

  Twelve Queries That Pass Every Schema Check and Still Return the Wrong Number

  Twelve query patterns that pass schema validation and still return wrong numbers, with detectors, required metadata, and tested code for each.

  AI AgentsSemantic LayerData Quality
• 30 MIN READ•Aug 19, 2026

  Goal-Directed Data Quality Agents: Anomaly Quarantine on Apache Iceberg

  Goal-directed data quality agents that watch Apache Iceberg tables, detect anomalies, and quarantine suspect data safely with snapshot isolation and branches.

  Apache Icebergdata qualityAI agents
• 30 MIN READ•Jul 25, 2026

  Freshness Is a Contract, Not a Note on a Dashboard

  How to turn data freshness into a contract with a measurable budget, an owner, and consequences, so AI agents know how old the numbers are before they act.

  data freshnessdata qualityapache iceberg
• 14 MIN READ•Jun 22, 2026

  The Context Layer for AI Agents

  AI agents need more than a semantic layer. Learn how to add lineage, quality, freshness, compliance, and ownership context, with guardrails and a rollout plan.

  AI metadatalineagedata quality
• 5 MIN READ•Feb 18, 2026

  Testing Data Pipelines: What to Validate and When

  What to test in a data pipeline and when: a testing pyramid for data, schema and contract tests, runtime validation, and regression and anomaly detection.

  data engineeringbest practicestesting
• 5 MIN READ•Feb 18, 2026

  Data Quality Is a Pipeline Problem, Not a Dashboard Problem

  When an analyst finds null values in a revenue column, the typical response is to add a calculated field in the BI tool - `IF revenue IS NULL THEN 0`.

  data engineeringbest practicesdata quality